At TeamStation AI, we are on a mission to bring together the brightest minds to solve tomorrow’s toughest technology challenges. Our work is about more than just AI—it’s about building the future through collaboration and innovation. We believe that the key to solving the world’s most complex problems lies in aligning diverse talents and perspectives. Our AI-powered platform enables cutting-edge scientific and technical teams to work smarter, faster, and together. By joining us, you’ll help unlock new technological breakthroughs and drive innovation where it matters most.

Join the Mission at TeamStation AI!

Where do we come from? We are seeking visionaries, innovators, and problem solvers who thrive in fast-paced, collaborative environments. If you’re passionate about AI, technology, and solving critical challenges, we want to hear from you. Come be part of a team where your ideas can drive the future.

Senior Data Infrastructure Engineer

Location: Latin America (Remote)
Industry: SaaS · Real Estate Operations Platform (TeamStation AI Partner)

Why TeamStation AI Needs You

Our Amazon RDS is carrying too much weight—handling both high-volume transactions and analytical workloads across multiple tenants. It’s a classic bottleneck: expensive, fragile, and increasingly unsustainable.

We're re-architecting for scale and resilience. That means separating workloads, securing every data flow, and delivering the right data to the right place, reliably and in real-time. This role isn’t about BI dashboards or ad-hoc ETLs—it’s about designing and operating the systems that move and transform data at the infrastructure layer.

You’ll be joining a team supporting a leading real estate operations platform—powering inspections, compliance, task scheduling, and risk mitigation for thousands of properties across the U.S. Your work will directly impact how on-site teams and regional managers make decisions in real time.

What You’ll Do

• Design and implement the separation of transactional and analytical workloads using Change Data Capture without introducing risk or downtime
• Build secure pipelines with full encryption, access controls, and data anonymization
• Create batch and real-time streaming pipelines that support schema evolution, multi-tenant scaling, and high availability
• Build async and push-based data delivery systems using webhooks, SQS, and Kinesis—no polling allowed
• Integrate deeply into third-party APIs and internal services across an event-driven architecture
• Make deliberate trade-offs between cost, performance, latency, and flexibility
• Implement observability from day one, including logging, metrics, and alerting for pipeline health and anomaly detection

Tech Stack & Tools

• Languages: Python, SQL
• Data Streaming & CDC: Apache Kafka, Debezium, AWS DMS
• Storage & Analytics: Amazon Redshift, Amazon S3 + Athena, AWS Glue, Apache Spark
• Infrastructure & Monitoring: Terraform, AWS Lambda, Step Functions, Prometheus, Grafana, CloudWatch

What We’re Looking For

• 5+ years in data engineering, platform engineering, or infrastructure roles at scale
• Deep fluency in Python, with strong command of SQL and distributed data systems
• Proven experience building CDC pipelines and stream-based architectures with Kafka, Debezium, or AWS DMS
• Familiarity with designing and managing data lakes or warehouses using S3 + Athena or Redshift
• Track record of building and evolving multi-tenant data systems that maintain performance, isolation, and delivery guarantees
• Strong knowledge of data security, encryption, access control, and compliance practices
• Ability to implement and maintain observability systems that catch issues before users do
• Clear communicator who thrives in remote-first, async teams
• Must be based in Latin America and able to align with a US Central Time team schedule

Nice to Have

• Experience with Terraform, AWS CDK, or CloudFormation for infrastructure as code
• Integrated with BI/reporting platforms like Metabase, Power BI, or Tableau
• Experience designing event-driven systems with pub/sub architectures and schema registries
• Background in performance tuning for Spark jobs, streaming consumers, or large-scale SQL queries
• Startup experience—pragmatic, resourceful, and used to balancing speed with stability

What to Expect in the Interview

We keep interviews practical and focused. You’ll walk through architecture-level challenges that reflect what you’ll be doing in this role. We’ll cover topics like:

• Evaluating technology for scalability, performance, and flexibility
• Strategies for safely decoupling production workloads under pressure
• Building systems that support async delivery and schema variation
• Designing for observability and pipeline resilience
• Making performance-cost trade-offs that scale

If your idea of fun is making data systems secure, reliable, and invisible in all the best ways—let’s talk.